Overview

Dataset statistics

Number of variables26
Number of observations1325506
Missing cells10
Missing cells (%)< 0.1%
Duplicate rows5128
Duplicate rows (%)0.4%
Total size in memory603.7 MiB
Average record size in memory477.5 B

Variable types

Categorical4
Numeric20
Text2

Alerts

Dataset has 5128 (0.4%) duplicate rowsDuplicates
AIRLINE_AIRPORT_FLIGHTS_MONTH is highly overall correlated with AIRPORT_FLIGHTS_MONTH and 2 other fieldsHigh correlation
AIRLINE_FLIGHTS_MONTH is highly overall correlated with AVG_MONTHLY_PASS_AIRLINE and 2 other fieldsHigh correlation
AIRPORT_FLIGHTS_MONTH is highly overall correlated with AIRLINE_AIRPORT_FLIGHTS_MONTH and 2 other fieldsHigh correlation
AVG_MONTHLY_PASS_AIRLINE is highly overall correlated with AIRLINE_FLIGHTS_MONTH and 1 other fieldsHigh correlation
AVG_MONTHLY_PASS_AIRPORT is highly overall correlated with AIRLINE_AIRPORT_FLIGHTS_MONTH and 2 other fieldsHigh correlation
CARRIER_NAME is highly overall correlated with AIRLINE_FLIGHTS_MONTH and 1 other fieldsHigh correlation
CONCURRENT_FLIGHTS is highly overall correlated with AIRLINE_AIRPORT_FLIGHTS_MONTH and 2 other fieldsHigh correlation
DEP_TIME_BLK is highly overall correlated with SEGMENT_NUMBERHigh correlation
FLT_ATTENDANTS_PER_PASS is highly overall correlated with GROUND_SERV_PER_PASSHigh correlation
GROUND_SERV_PER_PASS is highly overall correlated with FLT_ATTENDANTS_PER_PASSHigh correlation
LATITUDE is highly overall correlated with TMAXHigh correlation
MONTH is highly overall correlated with AIRLINE_FLIGHTS_MONTHHigh correlation
SEGMENT_NUMBER is highly overall correlated with DEP_TIME_BLKHigh correlation
TMAX is highly overall correlated with LATITUDEHigh correlation
GROUND_SERV_PER_PASS is highly skewed (γ1 = 1151.256063)Skewed
FLT_ATTENDANTS_PER_PASS has 149154 (11.3%) zerosZeros
PRCP has 887506 (67.0%) zerosZeros
SNOW has 1233969 (93.1%) zerosZeros
SNWD has 1223259 (92.3%) zerosZeros

Reproduction

Analysis started2024-02-28 00:43:07.644143
Analysis finished2024-02-28 00:52:55.006410
Duration9 minutes and 47.36 seconds
Software versionydata-profiling vv4.6.5
Download configurationconfig.json

Variables

MONTH
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size73.3 MiB
1
502050 
2
451439 
3
372017 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1325506
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 502050
37.9%
2 451439
34.1%
3 372017
28.1%

Length

2024-02-28T00:52:55.169502image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-02-28T00:52:55.437602image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
1 502050
37.9%
2 451439
34.1%
3 372017
28.1%

Most occurring characters

ValueCountFrequency (%)
1 502050
37.9%
2 451439
34.1%
3 372017
28.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1325506
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 502050
37.9%
2 451439
34.1%
3 372017
28.1%

Most occurring scripts

ValueCountFrequency (%)
Common 1325506
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 502050
37.9%
2 451439
34.1%
3 372017
28.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1325506
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 502050
37.9%
2 451439
34.1%
3 372017
28.1%

DAY_OF_WEEK
Real number (ℝ)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.9419829
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.1 MiB
2024-02-28T00:52:55.621661image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q36
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)4

Descriptive statistics

Standard deviation1.9664433
Coefficient of variation (CV)0.49884623
Kurtosis-1.18908
Mean3.9419829
Median Absolute Deviation (MAD)2
Skewness0.052865142
Sum5225122
Variance3.8668993
MonotonicityNot monotonic
2024-02-28T00:52:55.801322image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
4 207848
15.7%
5 197966
14.9%
2 197012
14.9%
3 194431
14.7%
1 185039
14.0%
7 182284
13.8%
6 160926
12.1%
ValueCountFrequency (%)
1 185039
14.0%
2 197012
14.9%
3 194431
14.7%
4 207848
15.7%
5 197966
14.9%
6 160926
12.1%
7 182284
13.8%
ValueCountFrequency (%)
7 182284
13.8%
6 160926
12.1%
5 197966
14.9%
4 207848
15.7%
3 194431
14.7%
2 197012
14.9%
1 185039
14.0%

DEP_DEL15
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size73.3 MiB
0
1075425 
1
250081 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1325506
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1075425
81.1%
1 250081
 
18.9%

Length

2024-02-28T00:52:56.039426image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-02-28T00:52:56.273203image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
0 1075425
81.1%
1 250081
 
18.9%

Most occurring characters

ValueCountFrequency (%)
0 1075425
81.1%
1 250081
 
18.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1325506
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1075425
81.1%
1 250081
 
18.9%

Most occurring scripts

ValueCountFrequency (%)
Common 1325506
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1075425
81.1%
1 250081
 
18.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1325506
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1075425
81.1%
1 250081
 
18.9%

DEP_TIME_BLK
Categorical

HIGH CORRELATION 

Distinct19
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size83.4 MiB
0800-0859
93492 
0700-0759
 
87225
1100-1159
 
82393
0600-0659
 
82373
1000-1059
 
82094
Other values (14)
897929 

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters11929554
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0800-0859
2nd row0700-0759
3rd row0600-0659
4th row0600-0659
5th row0001-0559

Common Values

ValueCountFrequency (%)
0800-0859 93492
 
7.1%
0700-0759 87225
 
6.6%
1100-1159 82393
 
6.2%
0600-0659 82373
 
6.2%
1000-1059 82094
 
6.2%
1700-1759 82089
 
6.2%
1200-1259 81956
 
6.2%
0900-0959 81696
 
6.2%
1800-1859 80817
 
6.1%
1500-1559 80550
 
6.1%
Other values (9) 490821
37.0%

Length

2024-02-28T00:52:56.464191image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0800-0859 93492
 
7.1%
0700-0759 87225
 
6.6%
1100-1159 82393
 
6.2%
0600-0659 82373
 
6.2%
1000-1059 82094
 
6.2%
1700-1759 82089
 
6.2%
1200-1259 81956
 
6.2%
0900-0959 81696
 
6.2%
1800-1859 80817
 
6.1%
1500-1559 80550
 
6.1%
Other values (9) 490821
37.0%

Most occurring characters

ValueCountFrequency (%)
0 3695144
31.0%
1 1874627
15.7%
9 1639928
13.7%
5 1515131
12.7%
- 1325506
 
11.1%
2 549618
 
4.6%
8 348618
 
2.9%
7 338628
 
2.8%
6 320398
 
2.7%
3 162792
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10604048
88.9%
Dash Punctuation 1325506
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3695144
34.8%
1 1874627
17.7%
9 1639928
15.5%
5 1515131
14.3%
2 549618
 
5.2%
8 348618
 
3.3%
7 338628
 
3.2%
6 320398
 
3.0%
3 162792
 
1.5%
4 159164
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 1325506
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11929554
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3695144
31.0%
1 1874627
15.7%
9 1639928
13.7%
5 1515131
12.7%
- 1325506
 
11.1%
2 549618
 
4.6%
8 348618
 
2.9%
7 338628
 
2.8%
6 320398
 
2.7%
3 162792
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11929554
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3695144
31.0%
1 1874627
15.7%
9 1639928
13.7%
5 1515131
12.7%
- 1325506
 
11.1%
2 549618
 
4.6%
8 348618
 
2.9%
7 338628
 
2.8%
6 320398
 
2.7%
3 162792
 
1.4%

DISTANCE_GROUP
Real number (ℝ)

Distinct11
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.851883
Minimum1
Maximum11
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.1 MiB
2024-02-28T00:52:56.666296image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q35
95-th percentile9
Maximum11
Range10
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.3790799
Coefficient of variation (CV)0.61764074
Kurtosis1.0536552
Mean3.851883
Median Absolute Deviation (MAD)1
Skewness1.197864
Sum5105694
Variance5.660021
MonotonicityNot monotonic
2024-02-28T00:52:56.869497image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
2 307832
23.2%
3 260400
19.6%
4 212228
16.0%
5 156299
11.8%
1 146498
11.1%
6 63959
 
4.8%
7 59050
 
4.5%
10 37659
 
2.8%
8 31466
 
2.4%
11 27734
 
2.1%
ValueCountFrequency (%)
1 146498
11.1%
2 307832
23.2%
3 260400
19.6%
4 212228
16.0%
5 156299
11.8%
6 63959
 
4.8%
7 59050
 
4.5%
8 31466
 
2.4%
9 22381
 
1.7%
10 37659
 
2.8%
ValueCountFrequency (%)
11 27734
 
2.1%
10 37659
 
2.8%
9 22381
 
1.7%
8 31466
 
2.4%
7 59050
 
4.5%
6 63959
 
4.8%
5 156299
11.8%
4 212228
16.0%
3 260400
19.6%
2 307832
23.2%

SEGMENT_NUMBER
Real number (ℝ)

HIGH CORRELATION 

Distinct15
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.9416932
Minimum1
Maximum15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.1 MiB
2024-02-28T00:52:57.092584image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile6
Maximum15
Range14
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.6928142
Coefficient of variation (CV)0.57545574
Kurtosis0.50273821
Mean2.9416932
Median Absolute Deviation (MAD)1
Skewness0.8400464
Sum3899232
Variance2.86562
MonotonicityNot monotonic
2024-02-28T00:52:57.286746image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
2 323920
24.4%
1 309313
23.3%
3 241359
18.2%
4 217395
16.4%
5 112107
 
8.5%
6 83674
 
6.3%
7 21923
 
1.7%
8 13132
 
1.0%
9 1165
 
0.1%
10 682
 
0.1%
Other values (5) 836
 
0.1%
ValueCountFrequency (%)
1 309313
23.3%
2 323920
24.4%
3 241359
18.2%
4 217395
16.4%
5 112107
 
8.5%
6 83674
 
6.3%
7 21923
 
1.7%
8 13132
 
1.0%
9 1165
 
0.1%
10 682
 
0.1%
ValueCountFrequency (%)
15 11
 
< 0.1%
14 73
 
< 0.1%
13 157
 
< 0.1%
12 248
 
< 0.1%
11 347
 
< 0.1%
10 682
 
0.1%
9 1165
 
0.1%
8 13132
 
1.0%
7 21923
 
1.7%
6 83674
6.3%

CONCURRENT_FLIGHTS
Real number (ℝ)

HIGH CORRELATION 

Distinct94
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27.727211
Minimum1
Maximum94
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.1 MiB
2024-02-28T00:52:57.556584image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4
Q112
median24
Q338
95-th percentile68
Maximum94
Range93
Interquartile range (IQR)26

Descriptive statistics

Standard deviation20.072428
Coefficient of variation (CV)0.72392525
Kurtosis0.26306951
Mean27.727211
Median Absolute Deviation (MAD)13
Skewness0.95580744
Sum36752585
Variance402.90238
MonotonicityNot monotonic
2024-02-28T00:52:57.823761image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9 38565
 
2.9%
10 37880
 
2.9%
11 36751
 
2.8%
8 36608
 
2.8%
5 33250
 
2.5%
6 33156
 
2.5%
12 32619
 
2.5%
7 32479
 
2.5%
26 31200
 
2.4%
14 31164
 
2.4%
Other values (84) 981834
74.1%
ValueCountFrequency (%)
1 7289
 
0.5%
2 17838
1.3%
3 25509
1.9%
4 30753
2.3%
5 33250
2.5%
6 33156
2.5%
7 32479
2.5%
8 36608
2.8%
9 38565
2.9%
10 37880
2.9%
ValueCountFrequency (%)
94 282
 
< 0.1%
93 465
 
< 0.1%
92 460
 
< 0.1%
91 728
 
0.1%
90 720
 
0.1%
89 2047
0.2%
88 968
 
0.1%
87 2436
0.2%
86 1720
0.1%
85 2720
0.2%

NUMBER_OF_SEATS
Real number (ℝ)

Distinct80
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean133.72497
Minimum44
Maximum337
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.1 MiB
2024-02-28T00:52:58.091657image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum44
5-th percentile50
Q190
median143
Q3172
95-th percentile191
Maximum337
Range293
Interquartile range (IQR)82

Descriptive statistics

Standard deviation46.763755
Coefficient of variation (CV)0.34970099
Kurtosis-0.25873155
Mean133.72497
Median Absolute Deviation (MAD)32
Skewness-0.125496
Sum1.7725325 × 108
Variance2186.8488
MonotonicityNot monotonic
2024-02-28T00:52:58.356143image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
143 182092
 
13.7%
76 149768
 
11.3%
50 78143
 
5.9%
175 70201
 
5.3%
160 69013
 
5.2%
129 53773
 
4.1%
181 38554
 
2.9%
70 36399
 
2.7%
173 34643
 
2.6%
187 33875
 
2.6%
Other values (70) 579045
43.7%
ValueCountFrequency (%)
44 15111
 
1.1%
50 78143
5.9%
65 1311
 
0.1%
66 26926
 
2.0%
69 8051
 
0.6%
70 36399
 
2.7%
76 149768
11.3%
79 10085
 
0.8%
90 20641
 
1.6%
99 7092
 
0.5%
ValueCountFrequency (%)
337 363
 
< 0.1%
306 4
 
< 0.1%
304 33
 
< 0.1%
294 2151
0.2%
293 881
 
0.1%
291 2655
0.2%
288 93
 
< 0.1%
285 416
 
< 0.1%
276 225
 
< 0.1%
273 1342
0.1%

CARRIER_NAME
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size98.0 MiB
Southwest Airlines Co.
254526 
American Airlines Inc.
205816 
Delta Air Lines Inc.
181729 
United Air Lines Inc.
122329 
SkyWest Airlines Inc.
114972 
Other values (12)
446134 

Length

Max length28
Median length27
Mean length20.546044
Min length11

Characters and Unicode

Total characters27233905
Distinct characters37
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSouthwest Airlines Co.
2nd rowDelta Air Lines Inc.
3rd rowDelta Air Lines Inc.
4th rowDelta Air Lines Inc.
5th rowSpirit Air Lines

Common Values

ValueCountFrequency (%)
Southwest Airlines Co. 254526
19.2%
American Airlines Inc. 205816
15.5%
Delta Air Lines Inc. 181729
13.7%
United Air Lines Inc. 122329
9.2%
SkyWest Airlines Inc. 114972
8.7%
Midwest Airline, Inc. 62454
 
4.7%
JetBlue Airways 59301
 
4.5%
Alaska Airlines Inc. 49302
 
3.7%
American Eagle Airlines Inc. 47611
 
3.6%
Comair Inc. 45876
 
3.5%
Other values (7) 181590
13.7%

Length

2024-02-28T00:52:58.639358image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
inc 943048
22.4%
airlines 767511
18.2%
air 390364
9.3%
lines 341399
 
8.1%
southwest 254526
 
6.0%
co 254526
 
6.0%
american 253427
 
6.0%
delta 181729
 
4.3%
united 122329
 
2.9%
skywest 114972
 
2.7%
Other values (15) 591719
14.0%

Most occurring characters

ValueCountFrequency (%)
i 3086312
11.3%
2890044
 
10.6%
n 2596474
 
9.5%
e 2459514
 
9.0%
s 1711238
 
6.3%
r 1701303
 
6.2%
A 1613649
 
5.9%
c 1220305
 
4.5%
t 1211720
 
4.4%
l 1206658
 
4.4%
Other values (27) 7536688
27.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 18694010
68.6%
Uppercase Letter 4389823
 
16.1%
Space Separator 2890044
 
10.6%
Other Punctuation 1260028
 
4.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 3086312
16.5%
n 2596474
13.9%
e 2459514
13.2%
s 1711238
9.2%
r 1701303
9.1%
c 1220305
 
6.5%
t 1211720
 
6.5%
l 1206658
 
6.5%
a 856363
 
4.6%
o 642025
 
3.4%
Other values (10) 2002098
10.7%
Uppercase Letter
ValueCountFrequency (%)
A 1613649
36.8%
I 943048
21.5%
S 430669
 
9.8%
L 341399
 
7.8%
C 300402
 
6.8%
D 181729
 
4.1%
U 122329
 
2.8%
W 114972
 
2.6%
M 100397
 
2.3%
E 89116
 
2.0%
Other values (4) 152113
 
3.5%
Other Punctuation
ValueCountFrequency (%)
. 1197574
95.0%
, 62454
 
5.0%
Space Separator
ValueCountFrequency (%)
2890044
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 23083833
84.8%
Common 4150072
 
15.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 3086312
13.4%
n 2596474
11.2%
e 2459514
10.7%
s 1711238
 
7.4%
r 1701303
 
7.4%
A 1613649
 
7.0%
c 1220305
 
5.3%
t 1211720
 
5.2%
l 1206658
 
5.2%
I 943048
 
4.1%
Other values (24) 5333612
23.1%
Common
ValueCountFrequency (%)
2890044
69.6%
. 1197574
28.9%
, 62454
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27233905
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 3086312
11.3%
2890044
 
10.6%
n 2596474
 
9.5%
e 2459514
 
9.0%
s 1711238
 
6.3%
r 1701303
 
6.2%
A 1613649
 
5.9%
c 1220305
 
4.5%
t 1211720
 
4.4%
l 1206658
 
4.4%
Other values (27) 7536688
27.7%

AIRPORT_FLIGHTS_MONTH
Real number (ℝ)

HIGH CORRELATION 

Distinct246
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12358.041
Minimum1118
Maximum33799
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.1 MiB
2024-02-28T00:52:58.901140image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1118
5-th percentile1751
Q15464
median11206
Q317206
95-th percentile28011
Maximum33799
Range32681
Interquartile range (IQR)11742

Descriptive statistics

Standard deviation7982.8981
Coefficient of variation (CV)0.64596792
Kurtosis-0.10264803
Mean12358.041
Median Absolute Deviation (MAD)5869
Skewness0.7241366
Sum1.6380658 × 1010
Variance63726662
MonotonicityNot monotonic
2024-02-28T00:52:59.209491image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30842 30842
 
2.3%
28011 28011
 
2.1%
27137 27137
 
2.0%
23912 23912
 
1.8%
23400 23400
 
1.8%
22775 22775
 
1.7%
22752 22752
 
1.7%
33799 22613
 
1.7%
20700 20700
 
1.6%
19559 19559
 
1.5%
Other values (236) 1083805
81.8%
ValueCountFrequency (%)
1118 149
 
< 0.1%
1133 104
 
< 0.1%
1134 2268
0.2%
1135 1135
0.1%
1141 764
 
0.1%
1160 1160
0.1%
1176 116
 
< 0.1%
1181 41
 
< 0.1%
1190 1190
0.1%
1191 1191
0.1%
ValueCountFrequency (%)
33799 22613
1.7%
30842 30842
2.3%
28011 28011
2.1%
27137 27137
2.0%
23912 23912
1.8%
23400 23400
1.8%
22775 22775
1.7%
22752 22752
1.7%
20700 20700
1.6%
19559 19559
1.5%

AIRLINE_FLIGHTS_MONTH
Real number (ℝ)

HIGH CORRELATION 

Distinct51
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean58187.945
Minimum6020
Maximum114119
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.1 MiB
2024-02-28T00:52:59.627440image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum6020
5-th percentile13447
Q123463
median67273
Q378308
95-th percentile107363
Maximum114119
Range108099
Interquartile range (IQR)54845

Descriptive statistics

Standard deviation32130.645
Coefficient of variation (CV)0.55218732
Kurtosis-1.2262423
Mean58187.945
Median Absolute Deviation (MAD)27649
Skewness0.049262091
Sum7.712847 × 1010
Variance1.0323784 × 109
MonotonicityNot monotonic
2024-02-28T00:53:00.170965image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
107363 104109
 
7.9%
94922 91669
 
6.9%
75506 73401
 
5.5%
73508 69096
 
5.2%
70199 67984
 
5.1%
78308 64431
 
4.9%
67273 62398
 
4.7%
114119 58748
 
4.4%
84142 50235
 
3.8%
46218 44465
 
3.4%
Other values (41) 638970
48.2%
ValueCountFrequency (%)
6020 4326
0.3%
6713 2331
 
0.2%
6791 6319
0.5%
6850 1104
 
0.1%
7180 2348
 
0.2%
8643 7772
0.6%
9496 8580
0.6%
9663 5410
0.4%
10218 2781
 
0.2%
10920 7916
0.6%
ValueCountFrequency (%)
114119 58748
4.4%
107363 104109
7.9%
94922 91669
6.9%
84142 50235
3.8%
78308 64431
4.9%
75506 73401
5.5%
73508 69096
5.2%
70199 67984
5.1%
68810 30819
 
2.3%
67273 62398
4.7%

AIRLINE_AIRPORT_FLIGHTS_MONTH
Real number (ℝ)

HIGH CORRELATION 

Distinct1001
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3304.6897
Minimum1
Maximum21165
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.1 MiB
2024-02-28T00:53:00.654609image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile143
Q1687
median2257
Q34441
95-th percentile11800
Maximum21165
Range21164
Interquartile range (IQR)3754

Descriptive statistics

Standard deviation3953.6759
Coefficient of variation (CV)1.1963834
Kurtosis7.45896
Mean3304.6897
Median Absolute Deviation (MAD)1717
Skewness2.5687938
Sum4.3803861 × 109
Variance15631553
MonotonicityNot monotonic
2024-02-28T00:53:01.146514image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18809 18809
 
1.4%
17181 17181
 
1.3%
21165 14154
 
1.1%
12140 12140
 
0.9%
11800 11800
 
0.9%
10835 10835
 
0.8%
8225 8225
 
0.6%
8156 8156
 
0.6%
7717 7717
 
0.6%
7439 7439
 
0.6%
Other values (991) 1209050
91.2%
ValueCountFrequency (%)
1 10
 
< 0.1%
2 24
 
< 0.1%
3 19
 
< 0.1%
4 61
< 0.1%
5 33
 
< 0.1%
6 24
 
< 0.1%
7 44
 
< 0.1%
8 79
< 0.1%
9 128
< 0.1%
10 75
< 0.1%
ValueCountFrequency (%)
21165 14154
1.1%
18809 18809
1.4%
17181 17181
1.3%
12140 12140
0.9%
11800 11800
0.9%
10835 10835
0.8%
8225 8225
0.6%
8156 8156
0.6%
7717 7717
0.6%
7439 7439
 
0.6%

AVG_MONTHLY_PASS_AIRPORT
Real number (ℝ)

HIGH CORRELATION 

Distinct91
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1664973.4
Minimum74283
Maximum4365661
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.1 MiB
2024-02-28T00:53:01.656459image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum74283
5-th percentile197188
Q1732595
median1581456
Q32006675
95-th percentile4365661
Maximum4365661
Range4291378
Interquartile range (IQR)1274080

Descriptive statistics

Standard deviation1100598.6
Coefficient of variation (CV)0.66103076
Kurtosis0.05011855
Mean1664973.4
Median Absolute Deviation (MAD)801130
Skewness0.74459948
Sum2.2069322 × 1012
Variance1.2113173 × 1012
MonotonicityNot monotonic
2024-02-28T00:53:02.185315image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4365661 81466
 
6.1%
3103410 73289
 
5.5%
2907365 67387
 
5.1%
2006675 55576
 
4.2%
2780593 52154
 
3.9%
1690031 43370
 
3.3%
1827202 43258
 
3.3%
2743323 41351
 
3.1%
1208249 39760
 
3.0%
1908862 38812
 
2.9%
Other values (81) 789083
59.5%
ValueCountFrequency (%)
74283 41
 
< 0.1%
89733 1265
 
0.1%
90547 147
 
< 0.1%
90611 2973
0.2%
96822 104
 
< 0.1%
103338 4097
0.3%
105972 116
 
< 0.1%
106354 174
 
< 0.1%
106382 1314
 
0.1%
118923 2739
0.2%
ValueCountFrequency (%)
4365661 81466
6.1%
3103410 73289
5.5%
2907365 67387
5.1%
2780593 52154
3.9%
2743323 41351
3.1%
2006675 55576
4.2%
1960746 30178
 
2.3%
1908862 38812
2.9%
1903352 32985
2.5%
1827202 43258
3.3%

AVG_MONTHLY_PASS_AIRLINE
Real number (ℝ)

HIGH CORRELATION 

Distinct17
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7798027.5
Minimum473794
Maximum13382999
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.1 MiB
2024-02-28T00:53:02.666153image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum473794
5-th percentile1191889
Q12688839
median8501631
Q312460183
95-th percentile13382999
Maximum13382999
Range12909205
Interquartile range (IQR)9771344

Descriptive statistics

Standard deviation5034984.1
Coefficient of variation (CV)0.64567406
Kurtosis-1.7536551
Mean7798027.5
Median Absolute Deviation (MAD)4881368
Skewness-0.20727527
Sum1.0336332 × 1013
Variance2.5351065 × 1013
MonotonicityNot monotonic
2024-02-28T00:53:03.222281image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
13382999 254526
19.2%
11744595 205816
15.5%
12460183 181729
13.7%
8501631 122329
9.2%
3472966 114972
8.7%
1529740 62454
 
4.7%
3190369 59301
 
4.5%
2884187 49302
 
3.7%
1204766 47611
 
3.6%
1245396 45876
 
3.5%
Other values (7) 181590
13.7%
ValueCountFrequency (%)
473794 23830
 
1.8%
905990 11749
 
0.9%
1191889 37943
2.9%
1204766 47611
3.6%
1212846 41505
3.1%
1245396 45876
3.5%
1257616 7460
 
0.6%
1529740 62454
4.7%
1857122 21762
 
1.6%
2688839 37341
2.8%
ValueCountFrequency (%)
13382999 254526
19.2%
12460183 181729
13.7%
11744595 205816
15.5%
8501631 122329
9.2%
3472966 114972
8.7%
3190369 59301
 
4.5%
2884187 49302
 
3.7%
2688839 37341
 
2.8%
1857122 21762
 
1.6%
1529740 62454
 
4.7%

FLT_ATTENDANTS_PER_PASS
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct14
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.7504114 × 10-5
Minimum0
Maximum0.00034840767
Zeros149154
Zeros (%)11.3%
Negative0
Negative (%)0.0%
Memory size10.1 MiB
2024-02-28T00:53:03.682817image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13.4192674 × 10-5
median6.1782363 × 10-5
Q30.00014416588
95-th percentile0.00025380424
Maximum0.00034840767
Range0.00034840767
Interquartile range (IQR)0.00010997321

Descriptive statistics

Standard deviation8.6696057 × 10-5
Coefficient of variation (CV)0.88915281
Kurtosis0.84747595
Mean9.7504114 × 10-5
Median Absolute Deviation (MAD)5.2608639 × 10-5
Skewness1.1274097
Sum129.24229
Variance7.5162063 × 10-9
MonotonicityNot monotonic
2024-02-28T00:53:04.111768image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
6.178236301 × 10-5254526
19.2%
9.82082929 × 10-5205816
15.5%
0.000144165885 181729
13.7%
0 149154
11.3%
0.0002538042406 122329
9.2%
3.419267401 × 10-5114972
8.7%
1.252935819 × 10-662454
 
4.7%
0.0001600389255 59301
 
4.5%
3.233146157 × 10-549302
 
3.7%
0.0003484076656 47611
 
3.6%
Other values (4) 78312
 
5.9%
ValueCountFrequency (%)
0 149154
11.3%
1.252935819 × 10-662454
 
4.7%
9.173723926 × 10-637341
 
2.8%
1.325258006 × 10-57460
 
0.6%
3.233146157 × 10-549302
 
3.7%
3.419267401 × 10-5114972
8.7%
6.178236301 × 10-5254526
19.2%
9.82082929 × 10-5205816
15.5%
0.0001157256483 21762
 
1.6%
0.0001204942176 11749
 
0.9%
ValueCountFrequency (%)
0.0003484076656 47611
 
3.6%
0.0002538042406 122329
9.2%
0.0001600389255 59301
 
4.5%
0.000144165885 181729
13.7%
0.0001204942176 11749
 
0.9%
0.0001157256483 21762
 
1.6%
9.82082929 × 10-5205816
15.5%
6.178236301 × 10-5254526
19.2%
3.419267401 × 10-5114972
8.7%
3.233146157 × 10-549302
 
3.7%

GROUND_SERV_PER_PASS
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct18
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.00014415362
Minimum7.1346949 × 10-6
Maximum9.88
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.1 MiB
2024-02-28T00:53:04.565262image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum7.1346949 × 10-6
5-th percentile8.9998106 × 10-5
Q19.8894123 × 10-5
median0.00012465107
Q30.00017728722
95-th percentile0.00022898547
Maximum9.88
Range9.8799929
Interquartile range (IQR)7.8393096 × 10-5

Descriptive statistics

Standard deviation0.008581563
Coefficient of variation (CV)59.53068
Kurtosis1325429
Mean0.00014415362
Median Absolute Deviation (MAD)2.575695 × 10-5
Skewness1151.2561
Sum191.07649
Variance7.3643223 × 10-5
MonotonicityNot monotonic
2024-02-28T00:53:05.034561image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
9.88941231 × 10-5254525
19.2%
0.0001772872196 205816
15.5%
0.0001486602009 181729
13.7%
0.0002289854735 122329
9.2%
9.900278806 × 10-5114972
8.7%
0.0001238227442 62454
 
4.7%
0.0001268661761 59301
 
4.5%
0.0001746014497 49302
 
3.7%
0.0001068671517 47611
 
3.6%
8.999810569 × 10-545876
 
3.5%
Other values (8) 181591
13.7%
ValueCountFrequency (%)
7.134694872 × 10-621762
 
1.6%
8.999810569 × 10-545876
 
3.5%
9.131157116 × 10-537943
 
2.9%
9.351277617 × 10-541505
 
3.1%
9.88941231 × 10-5254525
19.2%
9.900278806 × 10-5114972
8.7%
0.0001068671517 47611
 
3.6%
0.0001077434759 7460
 
0.6%
0.0001238227442 62454
 
4.7%
0.0001246510731 37341
 
2.8%
ValueCountFrequency (%)
9.88 1
 
< 0.1%
0.0002289854735 122329
9.2%
0.0001998053657 23830
 
1.8%
0.0001978496657 11749
 
0.9%
0.0001772872196 205816
15.5%
0.0001746014497 49302
 
3.7%
0.0001486602009 181729
13.7%
0.0001268661761 59301
 
4.5%
0.0001246510731 37341
 
2.8%
0.0001238227442 62454
 
4.7%

PLANE_AGE
Real number (ℝ)

Distinct33
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean11.568694
Minimum0
Maximum32
Zeros3707
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size10.1 MiB
2024-02-28T00:53:05.539532image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q15
median12
Q317
95-th percentile21
Maximum32
Range32
Interquartile range (IQR)12

Descriptive statistics

Standard deviation6.821751
Coefficient of variation (CV)0.58967338
Kurtosis-0.87345113
Mean11.568694
Median Absolute Deviation (MAD)6
Skewness0.13049367
Sum15334362
Variance46.536286
MonotonicityNot monotonic
2024-02-28T00:53:06.055365image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
11 108082
 
8.2%
18 84955
 
6.4%
3 82216
 
6.2%
5 77698
 
5.9%
15 76464
 
5.8%
4 71684
 
5.4%
2 71012
 
5.4%
19 67209
 
5.1%
14 65757
 
5.0%
1 63734
 
4.8%
Other values (23) 556694
42.0%
ValueCountFrequency (%)
0 3707
 
0.3%
1 63734
4.8%
2 71012
5.4%
3 82216
6.2%
4 71684
5.4%
5 77698
5.9%
6 47186
3.6%
7 32443
 
2.4%
8 27920
 
2.1%
9 26760
 
2.0%
ValueCountFrequency (%)
32 557
 
< 0.1%
31 812
 
0.1%
30 100
 
< 0.1%
29 4982
0.4%
28 7317
0.6%
27 12000
0.9%
26 4929
0.4%
25 5427
0.4%
24 6510
0.5%
23 8880
0.7%
Distinct91
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Memory size103.1 MiB
2024-02-28T00:53:07.095237image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length42
Median length33
Mean length24.526471
Min length7

Characters and Unicode

Total characters32509960
Distinct characters49
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMcCarran International
2nd rowMcCarran International
3rd rowMcCarran International
4th rowMcCarran International
5th rowMcCarran International
ValueCountFrequency (%)
international 884585
24.6%
municipal 139781
 
3.9%
fort 93187
 
2.6%
chicago 84762
 
2.4%
atlanta 81466
 
2.3%
dallas 79246
 
2.2%
san 76508
 
2.1%
o'hare 73289
 
2.0%
regional 67428
 
1.9%
worth 67387
 
1.9%
Other values (145) 1943580
54.1%
2024-02-28T00:53:08.735476image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 4251180
13.1%
a 3879141
11.9%
t 2949499
 
9.1%
o 2385303
 
7.3%
2265714
 
7.0%
l 2214220
 
6.8%
i 2204992
 
6.8%
e 2113470
 
6.5%
r 1884148
 
5.8%
I 939458
 
2.9%
Other values (39) 7422835
22.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 26137922
80.4%
Uppercase Letter 3849992
 
11.8%
Space Separator 2265714
 
7.0%
Other Punctuation 143832
 
0.4%
Dash Punctuation 112500
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 4251180
16.3%
a 3879141
14.8%
t 2949499
11.3%
o 2385303
9.1%
l 2214220
8.5%
i 2204992
8.4%
e 2113470
8.1%
r 1884148
7.2%
s 647737
 
2.5%
u 549478
 
2.1%
Other values (14) 3058754
11.7%
Uppercase Letter
ValueCountFrequency (%)
I 939458
24.4%
M 301402
 
7.8%
S 290317
 
7.5%
L 269675
 
7.0%
F 230530
 
6.0%
C 225996
 
5.9%
H 218961
 
5.7%
D 207260
 
5.4%
A 193886
 
5.0%
W 170227
 
4.4%
Other values (10) 802280
20.8%
Other Punctuation
ValueCountFrequency (%)
' 73289
51.0%
. 46037
32.0%
/ 24506
 
17.0%
Space Separator
ValueCountFrequency (%)
2265714
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 112500
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 29987914
92.2%
Common 2522046
 
7.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 4251180
14.2%
a 3879141
12.9%
t 2949499
9.8%
o 2385303
 
8.0%
l 2214220
 
7.4%
i 2204992
 
7.4%
e 2113470
 
7.0%
r 1884148
 
6.3%
I 939458
 
3.1%
s 647737
 
2.2%
Other values (34) 6518766
21.7%
Common
ValueCountFrequency (%)
2265714
89.8%
- 112500
 
4.5%
' 73289
 
2.9%
. 46037
 
1.8%
/ 24506
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 32509960
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 4251180
13.1%
a 3879141
11.9%
t 2949499
 
9.1%
o 2385303
 
7.3%
2265714
 
7.0%
l 2214220
 
6.8%
i 2204992
 
6.8%
e 2113470
 
6.5%
r 1884148
 
5.8%
I 939458
 
2.9%
Other values (39) 7422835
22.8%

LATITUDE
Real number (ℝ)

HIGH CORRELATION 

Distinct91
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean36.44757
Minimum18.44
Maximum61.169
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.1 MiB
2024-02-28T00:53:09.300369image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum18.44
5-th percentile26.536
Q132.899
median36.127
Q340.696
95-th percentile44.886
Maximum61.169
Range42.729
Interquartile range (IQR)7.797

Descriptive statistics

Standard deviation5.4086796
Coefficient of variation (CV)0.14839616
Kurtosis0.44455872
Mean36.44757
Median Absolute Deviation (MAD)3.647
Skewness-0.13333243
Sum48311437
Variance29.253815
MonotonicityNot monotonic
2024-02-28T00:53:09.818197image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.641 81466
 
6.1%
41.978 73289
 
5.5%
32.894 67387
 
5.1%
35.219 55576
 
4.2%
33.942 52154
 
3.9%
29.983 43370
 
3.3%
33.436 43258
 
3.3%
39.774 41351
 
3.1%
40.779 39760
 
3.0%
37.619 38812
 
2.9%
Other values (81) 789082
59.5%
ValueCountFrequency (%)
18.44 84
 
< 0.1%
19.739 1235
 
0.1%
20.901 4099
 
0.3%
21.319 8090
 
0.6%
21.979 1134
 
0.1%
25.792 21158
1.6%
26.074 25800
1.9%
26.536 8849
 
0.7%
26.682 5182
 
0.4%
27.973 14864
1.1%
ValueCountFrequency (%)
61.169 2798
 
0.2%
47.447 30178
2.3%
45.589 10928
 
0.8%
44.886 28324
2.1%
43.565 3461
 
0.3%
43.142 104
 
< 0.1%
43.121 174
 
< 0.1%
43.111 116
 
< 0.1%
42.95 4946
 
0.4%
42.941 3766
 
0.3%

LONGITUDE
Real number (ℝ)

Distinct91
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean-93.749773
Minimum-159.346
Maximum-66.002
Zeros0
Zeros (%)0.0%
Negative1325505
Negative (%)> 99.9%
Memory size10.1 MiB
2024-02-28T00:53:10.138551image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum-159.346
5-th percentile-122.375
Q1-104.88
median-87.906
Q3-80.936
95-th percentile-73.777
Maximum-66.002
Range93.344
Interquartile range (IQR)23.944

Descriptive statistics

Standard deviation17.393212
Coefficient of variation (CV)-0.18552805
Kurtosis0.55057921
Mean-93.749773
Median Absolute Deviation (MAD)9.124
Skewness-0.9498473
Sum-1.2426579 × 108
Variance302.52384
MonotonicityNot monotonic
2024-02-28T00:53:10.424066image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-84.427 81466
 
6.1%
-87.906 73289
 
5.5%
-97.03 67387
 
5.1%
-80.936 55576
 
4.2%
-118.408 52154
 
3.9%
-95.34 43370
 
3.3%
-112.009 43258
 
3.3%
-104.88 41351
 
3.1%
-73.876 39760
 
3.0%
-122.375 38812
 
2.9%
Other values (81) 789082
59.5%
ValueCountFrequency (%)
-159.346 1134
 
0.1%
-157.922 8090
 
0.6%
-156.434 4099
 
0.3%
-156.046 1235
 
0.1%
-149.985 2798
 
0.2%
-122.595 10928
 
0.8%
-122.375 38812
2.9%
-122.306 30178
2.3%
-122.221 9371
 
0.7%
-121.941 10888
 
0.8%
ValueCountFrequency (%)
-66.002 84
 
< 0.1%
-71.006 33309
2.5%
-71.426 2617
 
0.2%
-72.683 4736
 
0.4%
-73.777 30796
2.3%
-73.805 149
 
< 0.1%
-73.876 39760
3.0%
-74.172 24425
1.8%
-75.249 26553
2.0%
-76.102 116
 
< 0.1%
Distinct343
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Memory size96.7 MiB
2024-02-28T00:53:10.949441image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length47
Median length39
Mean length19.474352
Min length4

Characters and Unicode

Total characters25813351
Distinct characters57
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st rowNONE
2nd rowNONE
3rd rowNONE
4th rowNONE
5th rowNONE
ValueCountFrequency (%)
international 644955
 
21.2%
none 309313
 
10.2%
municipal 77763
 
2.6%
regional 59745
 
2.0%
san 51313
 
1.7%
field 51180
 
1.7%
chicago 44418
 
1.5%
county 42986
 
1.4%
fort 42537
 
1.4%
atlanta 40807
 
1.3%
Other values (499) 1675701
55.1%
2024-02-28T00:53:11.763141image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 3132190
12.1%
a 2802555
 
10.9%
t 2159195
 
8.4%
o 1758112
 
6.8%
1715213
 
6.6%
e 1713098
 
6.6%
i 1693422
 
6.6%
l 1648940
 
6.4%
r 1448680
 
5.6%
N 701388
 
2.7%
Other values (47) 7040558
27.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 19740211
76.5%
Uppercase Letter 4166642
 
16.1%
Space Separator 1715213
 
6.6%
Other Punctuation 99636
 
0.4%
Dash Punctuation 91535
 
0.4%
Decimal Number 114
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 3132190
15.9%
a 2802555
14.2%
t 2159195
10.9%
o 1758112
8.9%
e 1713098
8.7%
i 1693422
8.6%
l 1648940
8.4%
r 1448680
7.3%
s 513189
 
2.6%
u 413910
 
2.1%
Other values (16) 2456920
12.4%
Uppercase Letter
ValueCountFrequency (%)
N 701388
16.8%
I 677537
16.3%
O 394267
9.5%
E 321689
 
7.7%
M 226065
 
5.4%
S 217022
 
5.2%
C 200748
 
4.8%
L 191317
 
4.6%
F 183231
 
4.4%
A 149558
 
3.6%
Other values (14) 903820
21.7%
Other Punctuation
ValueCountFrequency (%)
/ 36371
36.5%
' 33744
33.9%
. 29521
29.6%
Decimal Number
ValueCountFrequency (%)
1 57
50.0%
3 57
50.0%
Space Separator
ValueCountFrequency (%)
1715213
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 91535
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 23906853
92.6%
Common 1906498
 
7.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 3132190
13.1%
a 2802555
11.7%
t 2159195
 
9.0%
o 1758112
 
7.4%
e 1713098
 
7.2%
i 1693422
 
7.1%
l 1648940
 
6.9%
r 1448680
 
6.1%
N 701388
 
2.9%
I 677537
 
2.8%
Other values (40) 6171736
25.8%
Common
ValueCountFrequency (%)
1715213
90.0%
- 91535
 
4.8%
/ 36371
 
1.9%
' 33744
 
1.8%
. 29521
 
1.5%
1 57
 
< 0.1%
3 57
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25813351
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 3132190
12.1%
a 2802555
 
10.9%
t 2159195
 
8.4%
o 1758112
 
6.8%
1715213
 
6.6%
e 1713098
 
6.6%
i 1693422
 
6.6%
l 1648940
 
6.4%
r 1448680
 
5.6%
N 701388
 
2.7%
Other values (47) 7040558
27.3%

PRCP
Real number (ℝ)

ZEROS 

Distinct173
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.094691729
Minimum0
Maximum5.08
Zeros887506
Zeros (%)67.0%
Negative0
Negative (%)0.0%
Memory size10.1 MiB
2024-02-28T00:53:12.073914image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.04
95-th percentile0.61
Maximum5.08
Range5.08
Interquartile range (IQR)0.04

Descriptive statistics

Standard deviation0.2618796
Coefficient of variation (CV)2.7656017
Kurtosis32.680823
Mean0.094691729
Median Absolute Deviation (MAD)0
Skewness4.686449
Sum125514.36
Variance0.068580927
MonotonicityNot monotonic
2024-02-28T00:53:12.352870image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 887506
67.0%
0.01 56843
 
4.3%
0.03 23240
 
1.8%
0.02 21741
 
1.6%
0.05 21197
 
1.6%
0.04 16369
 
1.2%
0.06 15066
 
1.1%
0.1 13125
 
1.0%
0.07 12531
 
0.9%
0.09 10938
 
0.8%
Other values (163) 246949
 
18.6%
ValueCountFrequency (%)
0 887506
67.0%
0.01 56843
 
4.3%
0.02 21741
 
1.6%
0.03 23240
 
1.8%
0.04 16369
 
1.2%
0.05 21197
 
1.6%
0.06 15066
 
1.1%
0.07 12531
 
0.9%
0.08 8427
 
0.6%
0.09 10938
 
0.8%
ValueCountFrequency (%)
5.08 38
 
< 0.1%
4.6 121
 
< 0.1%
2.78 77
 
< 0.1%
2.69 414
< 0.1%
2.5 409
< 0.1%
2.46 46
 
< 0.1%
2.45 82
 
< 0.1%
2.32 361
< 0.1%
2.24 21
 
< 0.1%
2.16 269
< 0.1%

SNOW
Real number (ℝ)

ZEROS 

Distinct65
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.089552963
Minimum0
Maximum17.2
Zeros1233969
Zeros (%)93.1%
Negative0
Negative (%)0.0%
Memory size10.1 MiB
2024-02-28T00:53:12.628525image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0.3
Maximum17.2
Range17.2
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.52650977
Coefficient of variation (CV)5.8793116
Kurtosis143.35674
Mean0.089552963
Median Absolute Deviation (MAD)0
Skewness9.8927066
Sum118702.9
Variance0.27721254
MonotonicityNot monotonic
2024-02-28T00:53:12.936917image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1233969
93.1%
0.1 14926
 
1.1%
0.2 6997
 
0.5%
0.3 6755
 
0.5%
1 5660
 
0.4%
0.4 5481
 
0.4%
0.5 4568
 
0.3%
0.7 3475
 
0.3%
0.9 3448
 
0.3%
0.6 3269
 
0.2%
Other values (55) 36957
 
2.8%
ValueCountFrequency (%)
0 1233969
93.1%
0.1 14926
 
1.1%
0.2 6997
 
0.5%
0.3 6755
 
0.5%
0.4 5481
 
0.4%
0.5 4568
 
0.3%
0.6 3269
 
0.2%
0.7 3475
 
0.3%
0.8 2220
 
0.2%
0.9 3448
 
0.3%
ValueCountFrequency (%)
17.2 61
 
< 0.1%
13.6 2
 
< 0.1%
9.9 255
< 0.1%
8.3 61
 
< 0.1%
7.8 163
 
< 0.1%
7.7 272
< 0.1%
7.4 29
 
< 0.1%
7.1 100
 
< 0.1%
6.9 139
 
< 0.1%
6.8 592
< 0.1%

SNWD
Real number (ℝ)

ZEROS 

Distinct24
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.28022195
Minimum0
Maximum25.2
Zeros1223259
Zeros (%)92.3%
Negative0
Negative (%)0.0%
Memory size10.1 MiB
2024-02-28T00:53:13.194825image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum25.2
Range25.2
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.291634
Coefficient of variation (CV)4.6093247
Kurtosis64.309423
Mean0.28022195
Median Absolute Deviation (MAD)0
Skewness6.9444352
Sum371435.6
Variance1.6683183
MonotonicityNot monotonic
2024-02-28T00:53:13.431487image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0 1223259
92.3%
1.2 33443
 
2.5%
2 17539
 
1.3%
5.1 12493
 
0.9%
3.1 10786
 
0.8%
3.9 10411
 
0.8%
7.1 5105
 
0.4%
9.1 3203
 
0.2%
5.9 2459
 
0.2%
7.9 1954
 
0.1%
Other values (14) 4853
 
0.4%
ValueCountFrequency (%)
0 1223259
92.3%
1.2 33443
 
2.5%
2 17539
 
1.3%
3.1 10786
 
0.8%
3.9 10411
 
0.8%
5.1 12493
 
0.9%
5.9 2459
 
0.2%
7.1 5105
 
0.4%
7.9 1954
 
0.1%
9.1 3203
 
0.2%
ValueCountFrequency (%)
25.2 33
 
< 0.1%
22.8 64
 
< 0.1%
20.9 96
 
< 0.1%
20.1 123
 
< 0.1%
18.9 289
< 0.1%
18.1 43
 
< 0.1%
16.9 123
 
< 0.1%
16.1 231
< 0.1%
15 455
< 0.1%
14.2 265
< 0.1%

TMAX
Real number (ℝ)

HIGH CORRELATION 

Distinct95
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean55.819656
Minimum-10
Maximum90
Zeros84
Zeros (%)< 0.1%
Negative486
Negative (%)< 0.1%
Memory size10.1 MiB
2024-02-28T00:53:13.701853image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum-10
5-th percentile28
Q144
median57
Q368
95-th percentile82
Maximum90
Range100
Interquartile range (IQR)24

Descriptive statistics

Standard deviation16.728162
Coefficient of variation (CV)0.29968228
Kurtosis-0.4061831
Mean55.819656
Median Absolute Deviation (MAD)12
Skewness-0.2795527
Sum73989234
Variance279.8314
MonotonicityNot monotonic
2024-02-28T00:53:13.985374image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
60 37018
 
2.8%
61 34691
 
2.6%
59 34659
 
2.6%
62 33019
 
2.5%
56 32854
 
2.5%
58 32317
 
2.4%
65 31822
 
2.4%
63 31662
 
2.4%
66 29672
 
2.2%
54 28416
 
2.1%
Other values (85) 999375
75.4%
ValueCountFrequency (%)
-10 395
 
< 0.1%
-7 36
 
< 0.1%
-2 55
 
< 0.1%
0 84
 
< 0.1%
1 800
0.1%
2 23
 
< 0.1%
3 504
 
< 0.1%
4 122
 
< 0.1%
5 1475
0.1%
6 44
 
< 0.1%
ValueCountFrequency (%)
90 100
 
< 0.1%
89 615
 
< 0.1%
88 1047
 
0.1%
87 4052
 
0.3%
86 6460
 
0.5%
85 11519
0.9%
84 11640
0.9%
83 23238
1.8%
82 19731
1.5%
81 17823
1.3%

AWND
Real number (ℝ)

Distinct120
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean8.9686236
Minimum0
Maximum33.78
Zeros219
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size10.1 MiB
2024-02-28T00:53:14.257026image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.36
Q15.82
median8.28
Q311.41
95-th percentile16.55
Maximum33.78
Range33.78
Interquartile range (IQR)5.59

Descriptive statistics

Standard deviation4.1683795
Coefficient of variation (CV)0.46477361
Kurtosis1.1076523
Mean8.9686236
Median Absolute Deviation (MAD)2.69
Skewness0.89657741
Sum11887955
Variance17.375388
MonotonicityNot monotonic
2024-02-28T00:53:14.527268image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.61 42352
 
3.2%
4.92 41098
 
3.1%
6.71 39581
 
3.0%
10.51 38973
 
2.9%
8.5 37235
 
2.8%
5.82 36484
 
2.8%
6.93 34656
 
2.6%
7.38 31992
 
2.4%
8.05 31690
 
2.4%
4.7 31536
 
2.4%
Other values (110) 959908
72.4%
ValueCountFrequency (%)
0 219
 
< 0.1%
0.67 246
 
< 0.1%
0.89 134
 
< 0.1%
1.12 322
 
< 0.1%
1.34 602
 
< 0.1%
1.57 1836
 
0.1%
1.79 2615
 
0.2%
2.01 5522
0.4%
2.24 6586
0.5%
2.46 5457
0.4%
ValueCountFrequency (%)
33.78 65
 
< 0.1%
32.88 100
 
< 0.1%
30.42 95
 
< 0.1%
29.3 59
 
< 0.1%
28.63 122
 
< 0.1%
28.19 361
< 0.1%
27.96 57
 
< 0.1%
27.07 879
0.1%
26.62 785
0.1%
26.4 51
 
< 0.1%

Interactions

2024-02-28T00:52:28.130960image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-28T00:49:20.653227image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-28T00:49:30.017400image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-28T00:49:39.163642image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-28T00:49:49.855671image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-28T00:49:58.391029image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
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2024-02-28T00:51:44.081028image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-28T00:51:52.841410image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-28T00:52:02.830890image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-28T00:52:11.331400image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-28T00:52:24.208445image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-28T00:52:36.145803image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-28T00:49:26.997264image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-28T00:49:37.142247image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-28T00:49:46.950572image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-28T00:49:56.094963image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-28T00:50:06.869983image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-28T00:50:15.559230image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-28T00:50:27.394370image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-28T00:50:38.783517image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-28T00:50:46.812379image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-28T00:50:57.225811image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-28T00:51:05.994358image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
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2024-02-28T00:49:56.525379image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
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2024-02-28T00:50:16.181517image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-28T00:50:28.063399image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-28T00:50:39.178219image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-28T00:50:47.256409image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-28T00:50:57.668738image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-28T00:51:06.595105image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-28T00:51:16.527106image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-28T00:51:26.551092image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
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2024-02-28T00:51:44.821508image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-28T00:51:53.687165image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
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2024-02-28T00:51:35.332336image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
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2024-02-28T00:49:57.552486image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-28T00:50:08.253378image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-28T00:50:17.460697image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-28T00:50:29.291536image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
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2024-02-28T00:51:09.122428image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-28T00:51:17.757851image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-28T00:51:28.167927image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-28T00:51:36.140026image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-28T00:51:46.527855image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
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2024-02-28T00:52:04.932644image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-28T00:52:14.009473image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-28T00:52:27.546605image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Correlations

2024-02-28T00:53:14.802634image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
AIRLINE_AIRPORT_FLIGHTS_MONTHAIRLINE_FLIGHTS_MONTHAIRPORT_FLIGHTS_MONTHAVG_MONTHLY_PASS_AIRLINEAVG_MONTHLY_PASS_AIRPORTAWNDCARRIER_NAMECONCURRENT_FLIGHTSDAY_OF_WEEKDEP_DEL15DEP_TIME_BLKDISTANCE_GROUPFLT_ATTENDANTS_PER_PASSGROUND_SERV_PER_PASSLATITUDELONGITUDEMONTHNUMBER_OF_SEATSPLANE_AGEPRCPSEGMENT_NUMBERSNOWSNWDTMAX
AIRLINE_AIRPORT_FLIGHTS_MONTH1.0000.3040.6070.2670.6070.0240.3810.5650.0070.0520.102-0.0160.1620.106-0.032-0.0860.1540.1420.067-0.0170.080-0.016-0.0340.041
AIRLINE_FLIGHTS_MONTH0.3041.000-0.0230.928-0.035-0.0430.718-0.056-0.0020.0670.0420.0340.199-0.066-0.078-0.1050.5120.2850.146-0.0340.019-0.030-0.0260.057
AIRPORT_FLIGHTS_MONTH0.607-0.0231.000-0.0710.9500.0690.2400.8440.0180.0530.0800.0050.1110.142-0.025-0.0460.3070.0150.000-0.0340.062-0.022-0.0630.042
AVG_MONTHLY_PASS_AIRLINE0.2670.928-0.0711.000-0.045-0.0501.000-0.093-0.0080.0410.0650.1270.291-0.002-0.079-0.1290.0370.4600.163-0.006-0.024-0.022-0.0130.055
AVG_MONTHLY_PASS_AIRPORT0.607-0.0350.950-0.0451.0000.0530.2830.8030.0180.0510.0940.0540.1430.180-0.013-0.1420.0860.080-0.007-0.0140.039-0.020-0.0590.039
AWND0.024-0.0430.069-0.0500.0531.0000.0480.063-0.0240.0710.0130.0120.0490.0330.1790.1540.117-0.037-0.0020.192-0.0230.0870.039-0.166
CARRIER_NAME0.3810.7180.2401.0000.2830.0481.000-0.111-0.0040.0750.0570.0010.020-0.238-0.023-0.0830.057-0.0280.044-0.0150.0410.0210.0210.018
CONCURRENT_FLIGHTS0.565-0.0560.844-0.0930.8030.063-0.1111.000-0.0150.0240.171-0.0010.0780.1310.0130.0210.088-0.0340.019-0.0300.015-0.013-0.0390.010
DAY_OF_WEEK0.007-0.0020.018-0.0080.018-0.024-0.004-0.0151.0000.0390.0160.0210.0020.008-0.016-0.0050.0630.011-0.0070.042-0.0320.010-0.0220.048
DEP_DEL150.0520.0670.0530.0410.0510.0710.0750.0240.0391.0000.1550.014-0.002-0.0260.017-0.0020.052-0.0060.0040.0990.1110.0860.052-0.047
DEP_TIME_BLK0.1020.0420.0800.0650.0940.0130.0570.1710.0160.1551.000-0.071-0.018-0.026-0.0360.0120.024-0.0390.008-0.0050.765-0.007-0.0060.029
DISTANCE_GROUP-0.0160.0340.0050.1270.0540.0120.001-0.0010.0210.014-0.0711.0000.2230.259-0.023-0.0730.0160.466-0.156-0.015-0.241-0.009-0.0200.070
FLT_ATTENDANTS_PER_PASS0.1620.1990.1110.2910.1430.0490.0200.0780.002-0.002-0.0180.2231.0000.557-0.0260.0060.0490.3510.228-0.010-0.1280.012-0.0120.018
GROUND_SERV_PER_PASS0.106-0.0660.142-0.0020.1800.033-0.2380.1310.008-0.026-0.0260.2590.5571.000-0.008-0.0490.0010.3440.162-0.000-0.196-0.001-0.0180.044
LATITUDE-0.032-0.078-0.025-0.079-0.0130.179-0.0230.013-0.0160.017-0.036-0.023-0.026-0.0081.0000.1410.049-0.1350.0020.093-0.0180.2730.288-0.680
LONGITUDE-0.086-0.105-0.046-0.129-0.1420.154-0.0830.021-0.005-0.0020.012-0.0730.006-0.0490.1411.0000.059-0.1140.0280.017-0.0270.063-0.001-0.186
MONTH0.1540.5120.3070.0370.0860.1170.0570.0880.0630.0520.0240.0160.0490.0010.0490.0591.000-0.003-0.008-0.0170.021-0.066-0.1000.213
NUMBER_OF_SEATS0.1420.2850.0150.4600.080-0.037-0.028-0.0340.011-0.006-0.0390.4660.3510.344-0.135-0.114-0.0031.000-0.226-0.016-0.204-0.041-0.0500.136
PLANE_AGE0.0670.1460.0000.163-0.007-0.0020.0440.019-0.0070.0040.008-0.1560.2280.1620.0020.028-0.008-0.2261.0000.0050.0480.0010.005-0.015
PRCP-0.017-0.034-0.034-0.006-0.0140.192-0.015-0.0300.0420.099-0.005-0.015-0.010-0.0000.0930.017-0.017-0.0160.0051.000-0.0160.3010.078-0.105
SEGMENT_NUMBER0.0800.0190.062-0.0240.039-0.0230.0410.015-0.0320.1110.765-0.241-0.128-0.196-0.018-0.0270.021-0.2040.048-0.0161.000-0.013-0.0020.006
SNOW-0.016-0.030-0.022-0.022-0.0200.0870.021-0.0130.0100.086-0.007-0.0090.012-0.0010.2730.063-0.066-0.0410.0010.301-0.0131.0000.430-0.362
SNWD-0.034-0.026-0.063-0.013-0.0590.0390.021-0.039-0.0220.052-0.006-0.020-0.012-0.0180.288-0.001-0.100-0.0500.0050.078-0.0020.4301.000-0.385
TMAX0.0410.0570.0420.0550.039-0.1660.0180.0100.048-0.0470.0290.0700.0180.044-0.680-0.1860.2130.136-0.015-0.1050.006-0.362-0.3851.000

Missing values

2024-02-28T00:52:39.694704image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
A simple visualization of nullity by column.
2024-02-28T00:52:44.024108image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-02-28T00:52:53.231710image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

MONTHDAY_OF_WEEKDEP_DEL15DEP_TIME_BLKDISTANCE_GROUPSEGMENT_NUMBERCONCURRENT_FLIGHTSNUMBER_OF_SEATSCARRIER_NAMEAIRPORT_FLIGHTS_MONTHAIRLINE_FLIGHTS_MONTHAIRLINE_AIRPORT_FLIGHTS_MONTHAVG_MONTHLY_PASS_AIRPORTAVG_MONTHLY_PASS_AIRLINEFLT_ATTENDANTS_PER_PASSGROUND_SERV_PER_PASSPLANE_AGEDEPARTING_AIRPORTLATITUDELONGITUDEPREVIOUS_AIRPORTPRCPSNOWSNWDTMAXAWND
01700800-08592125143Southwest Airlines Co.1305610736358731903352133829990.0000620.0000998.0McCarran International36.08-115.152NONE0.00.00.065.02.91
11700700-07597129191Delta Air Lines Inc.130567350811741903352124601830.0001440.0001493.0McCarran International36.08-115.152NONE0.00.00.065.02.91
21700600-06597127199Delta Air Lines Inc.130567350811741903352124601830.0001440.00014918.0McCarran International36.08-115.152NONE0.00.00.065.02.91
31700600-06599127180Delta Air Lines Inc.130567350811741903352124601830.0001440.0001492.0McCarran International36.08-115.152NONE0.00.00.065.02.91
41700001-05597110182Spirit Air Lines13056150231257190335226888390.0000090.0001251.0McCarran International36.08-115.152NONE0.00.00.065.02.91
51700001-05593110180Frontier Airlines Inc.130569496581190335218571220.0001160.0000075.0McCarran International36.08-115.152NONE0.00.00.065.02.91
61700700-07596129186Frontier Airlines Inc.130569496581190335218571220.0001160.0000072.0McCarran International36.08-115.152NONE0.00.00.065.02.91
71710001-05597110186Frontier Airlines Inc.130569496581190335218571220.0001160.0000073.0McCarran International36.08-115.152NONE0.00.00.065.02.91
81700001-05597110180Frontier Airlines Inc.130569496581190335218571220.0001160.0000073.0McCarran International36.08-115.152NONE0.00.00.065.02.91
91700600-06598127186Frontier Airlines Inc.130569496581190335218571220.0001160.0000071.0McCarran International36.08-115.152NONE0.00.00.065.02.91
MONTHDAY_OF_WEEKDEP_DEL15DEP_TIME_BLKDISTANCE_GROUPSEGMENT_NUMBERCONCURRENT_FLIGHTSNUMBER_OF_SEATSCARRIER_NAMEAIRPORT_FLIGHTS_MONTHAIRLINE_FLIGHTS_MONTHAIRLINE_AIRPORT_FLIGHTS_MONTHAVG_MONTHLY_PASS_AIRPORTAVG_MONTHLY_PASS_AIRLINEFLT_ATTENDANTS_PER_PASSGROUND_SERV_PER_PASSPLANE_AGEDEPARTING_AIRPORTLATITUDELONGITUDEPREVIOUS_AIRPORTPRCPSNOWSNWDTMAXAWND
13254963600001-05594112143Southwest Airlines Co.68351141196398819756133829990.0000620.00009913.0Chicago Midway International41.785-87.752NONE0.560.00.043.014.09
13254973600001-05593112143Southwest Airlines Co.68351141196398819756133829990.0000620.00009910.0Chicago Midway International41.785-87.752NONE0.560.00.043.014.09
13254983612100-21591112143Southwest Airlines Co.68351141196398819756133829990.0000620.00009917.0Chicago Midway International41.785-87.752NONE0.560.00.043.014.09
13254993600900-09593112143Southwest Airlines Co.68351141196398819756133829990.0000620.00009915.0Chicago Midway International41.785-87.752NONE0.560.00.043.014.09
13255003600001-05595112143Southwest Airlines Co.68351141196398819756133829990.0000620.00009918.0Chicago Midway International41.785-87.752NONE0.560.00.043.014.09
13255013600001-05594112143Southwest Airlines Co.68351141196398819756133829990.0000620.00009916.0Chicago Midway International41.785-87.752NONE0.560.00.043.014.09
13255023600700-07592113143Southwest Airlines Co.68351141196398819756133829990.0000620.00009920.0Chicago Midway International41.785-87.752NONE0.560.00.043.014.09
13255033600001-05593112143Southwest Airlines Co.68351141196398819756133829990.0000620.00009911.0Chicago Midway International41.785-87.752NONE0.560.00.043.014.09
13255043601000-1059324110Delta Air Lines Inc.683584142184819756124601830.0001440.00014918.0Chicago Midway International41.785-87.752Atlanta Municipal0.560.00.043.014.09
13255053611300-13594221175Southwest Airlines Co.68351141196398819756133829990.0000629.880000NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN

Duplicate rows

Most frequently occurring

MONTHDAY_OF_WEEKDEP_DEL15DEP_TIME_BLKDISTANCE_GROUPSEGMENT_NUMBERCONCURRENT_FLIGHTSNUMBER_OF_SEATSCARRIER_NAMEAIRPORT_FLIGHTS_MONTHAIRLINE_FLIGHTS_MONTHAIRLINE_AIRPORT_FLIGHTS_MONTHAVG_MONTHLY_PASS_AIRPORTAVG_MONTHLY_PASS_AIRLINEFLT_ATTENDANTS_PER_PASSGROUND_SERV_PER_PASSPLANE_AGEDEPARTING_AIRPORTLATITUDELONGITUDEPREVIOUS_AIRPORTPRCPSNOWSNWDTMAXAWND# duplicates
5911300001-0559114690Comair Inc.18811224187248200667512453960.0000000.0000905.0Douglas Municipal35.219-80.936NONE0.100.00.058.05.146
24672201200-12593148129Atlantic Southeast Airlines1327210920301216900314737940.0000000.00020011.0Houston Intercontinental29.983-95.340NONE0.060.00.080.08.286
37683100600-0659419129Allegiant Air114110218114112519812576160.0000130.00010811.0Sanford NAS28.775-81.240NONE0.090.00.081.04.926
1501100700-07595128129Allegiant Air130566713645190335212576160.0000130.00010811.0McCarran International36.080-115.152NONE0.000.00.056.07.615
5651201200-12593151129Atlantic Southeast Airlines1450112231334716900314737940.0000000.00020011.0Houston Intercontinental29.983-95.340NONE0.010.00.079.011.865
21642100700-07595128129Allegiant Air115007180641190335212576160.0000130.00010811.0McCarran International36.080-115.152NONE0.000.00.059.03.365
29052400700-07595132129Allegiant Air115007180641190335212576160.0000130.00010811.0McCarran International36.080-115.152NONE0.000.00.074.011.635
30062410700-07595125129Allegiant Air115007180641190335212576160.0000130.00010811.0McCarran International36.080-115.152NONE0.210.30.044.02.245
35812700700-07595129129Allegiant Air115007180641190335212576160.0000130.00010811.0McCarran International36.080-115.152NONE0.000.00.057.02.245
37703100600-06594110129Allegiant Air114110218114112519812576160.0000130.00010811.0Sanford NAS28.775-81.240NONE0.000.00.067.05.145